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1. Fundamen6tals of Artificial Intelligence (IA)
- General introduction to AI
- History and evolution of AI
- Main AI concepts and terminology
- Differences between Machine Learning, Deep Learning, and other branches of AI
- Introduction to AI models and their general applications
- AI work environment: core tools, languages, and platforms
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2. Landscape of AI in the legal sector
- Introduction to AI applied to law: current developments and trends
- Benefits and challenges: efficiency, accuracy, cost savings
- Ethical and legal challenges
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3. New AI regulations
- Analysis of the EU Artificial Intelligence Act and other jurisdictions
- Implications for law firms: legal obligations and regulatory compliance
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4. Need for local AI in the areas of legal
- Benefits of on-premise solutions: data control and security
- Comparison with cloud solutions: associated risks and legal considerations
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5. Traceability and explainable AI models
- Importance of traceability: regulatory compliance and customer trust
- Techniques for explainable models: Explainable AI (XAI)
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6. Practical applications of AI in offices and departments
- Automation of repetitive tasks: document classification, case management
- Predictive analytics in litigation: predicting court outcomes
- Contract review and analysis: clause and risk detection
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7. Current tools and technologies
- AI software available: local solutions adapted to the legal sector
- Vendor evaluation: criteria for selecting compliant tools
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8. Implementation of AI in offices and departments
- Strategic planning: identification of needs and objectives
- Change management: staff training, process adaptation
- Success stories: studies of firms that have implemented AI locally
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9. Ethical and compliance considerations
- Bias and discrimination in AI: how to identify and mitigate them
- Professional responsability: ethics and best practices
- Transparency and informed consent: clear communication with customers
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10. Practical workshop I
- Developing a traceability AI model: steps to build and train the model
- Compliance analysis: verification of alignment with current regulations
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11. AI and data protection
- Privacy regulations: GDPR and its impact on AI
- Handling sensitive data: best practices and security mesures
- Impact evaluations: how to conduct them and their importance
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12. Future of AI in Law
- Emerging trends: generative AI and its potential in the legal industry
- Access to justice: how AI can democratize legal services
- The role of the lawyer in the age of AI: adaptation and new skills needed
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13. Final session: practical workshop II and conclusions
- Implementing a local AI project: working in groups to develop solutions
- Presentation and feedback: discussion of the projects and key learnings
- Next steps: additional resources and personal action plan
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